Alison Singer
President
Autism Science Foundation
From this contributor
It’s time to embrace ‘profound autism’
My experience at the Autism-Europe International Congress — and as a parent of a child with profound autism — makes me more convinced than ever that we need to bifurcate the diagnosis of ‘autism spectrum disorder’ and add a new diagnosis of ‘profound autism’ to better serve this vulnerable population.
Portrayals of autism on television don’t showcase full spectrum
Television characters with autism look dramatically different from the majority of people who have the condition.
Portrayals of autism on television don’t showcase full spectrum
The case for brain donation
We can't get back the tissue lost in the Harvard freezer malfunction, but we can try to create something positive from this tragic event, says Alison Singer.
Explore more from The Transmitter
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.